license: cc-by-4.0
language:
- tr
tags:
- Text-to-SQL
- NL2SQL
Dataset Card for TURSpider
TURSpider is a human curated variant of the Spider Text-to-SQL database.
The source GIT repo for TURSpider is located here: https://github.com/alibugra/TURSpider/
Paper Abstract
This paper introduces TURSpider, a novel Turkish Text-to-SQL dataset developed through human translation of the widely used Spider dataset, aimed at addressing the current lack of complex, cross-domain SQL datasets for the Turkish language. TURSpider incorporates a wide range of query difficulties, including nested queries, to create a comprehensive benchmark for Turkish Text-to-SQL tasks. The dataset enables cross-language comparison and significantly enhances the training and evaluation of large language models (LLMs) in generating SQL queries from Turkish natural language inputs. We fine-tuned several Turkish-supported LLMs on TURSpider and evaluated their performance in comparison to state-of-the-art models like GPT-3.5 Turbo and GPT-4. Our results show that fine-tuned Turkish LLMs demonstrate competitive performance, with one model even surpassing GPT-based models on execution accuracy. We also apply the Chain-of-Feedback (CoF) methodology to further improve model performance, demonstrating its effectiveness across multiple LLMs. This work provides a valuable resource for Turkish NLP and addresses specific challenges in developing accurate Text-to-SQL models for low-resource languages.
Citation Information
@ARTICLE{10753591,
author={Kanburoglu, Ali Bugra and Boray Tek, Faik},
journal={IEEE Access},
title={TURSpider: A Turkish Text-to-SQL Dataset and LLM-Based Study},
year={2024},
volume={12},
number={},
pages={169379-169387},
keywords={Training;Structured Query Language;Accuracy;Error analysis;Large language models;Benchmark testing;Cognition;Encoding;Text-to-SQL;LLM;large language models;Turkish;dataset;TURSpider},
doi={10.1109/ACCESS.2024.3498841}}